Abstract: This project report emphasis enhancement of power quality by using UPQC with fuzzy logic controller (FLC), Artificial Neural Network (ANN) controller and with the conventional proportionalintegral (PI) controller. The unified power quality conditioner (UPQC) is being used as a universal active power conditioning device to mitigate both current and voltage harmonics at a distribution s...

This paper presents the design of neural networks compared with the conventional technique, a hysteresis controller for active power filter for three-phase four-wire electric system. A particular three-layer neural network structure is studied in some detail. Simulation and experimental results of the active power filter with both controllers are also presented to verify the feasibility of such...

This paper addresses the issue of trajectory tracking control based on a neural network controller for industrial manipulators. A new control scheme is proposed based on neural network technology and linear feedback approach for tracking a planned trajectory. In detail, the control system is designed with two parallel subsystems designed separately. One is a linear controller, and another one i...

In this paper Hybrid Direct Neural Controller (HDNC) with Linear Feedback Compensator (LFBC) has been developed. Proper initialization of neural network weights is a critical problem. This paper presents two different neural network configurations with unity and random weight initialization while using it as a direct controller and linear feedback compensator. The performances of these controll...

Abstract The traditional PID controller is widely used to improve the stability of system because its simplicity and convenience. However, disadvantage control method that parameters are difficult adjust in real-time, it can not adapt needs variable targets different states, affecting controller’s practical application effect. Therefore, using idea hierarchical learning self-adjusting control, ...

In this paper, adaptive neural network sliding-mode controller design approach with decoupled method is proposed. The decoupled method provides a simple way to achieve asymptotic stability for a class of fourth-order nonlinear system. The adaptive neural sliding mode control system is comprised of neural network (NN) and a compensation controller. The NN is the main tracking controller, which i...

This paper deals with the designing of neural PID speed controller of Permanent Magnet synchronous Motor (PMSM). The conventional Proportional-Integral-Derivative (PID) controller is largely used in industry because of the robustness this regulator procures. ANN is developed controller in this work, offer inherent advantages over conventional PID controller for PMSM, Reduction of the effects of...

In this paper, a neural network based predictive controller is designed to govern the dynamics of a heat exchanger pilot plant. Heat exchanger is a highly nonlinear process; therefore, a nonlinear prediction method can be a better match in a predictive control strategy. Advantages of neural networks for the process modeling are studied and a neural network based predictor is designed, trained a...